Redhwan013's repositories
charts
Curated applications for Kubernetes
deep-learning-book
Repository for "Introduction to Artificial Neural Networks and Deep Learning: A Practical Guide with Applications in Python"
deep-mri-qc
This project is trained on private MRI data, where scans are marked QC_PASS or QC_FAIL. Several architectures of neural networks are explored to make automatic predictions for new images.
ElasticFusion
Real-time dense visual SLAM system
financial-data-analyzer
This is a C++ code that aims at finding patterns in financial data series. To find these patterns, the code uses Artificial Neural Networks implemented by FANN library.
FinancialRiskFactor
Computing financial risk factor and decrease in cost of functions using feed forward neural network(SGD)
Free-CSharp-Books
A curated collection of free C# and .NET eBooks
GridViewScroll
Freeze column and fixed header in Table or GridView
Image-recognition
Image recognition methods from bag of words (BoW), Spatial Pyramid Matching (SPM), Sparse Codeing SPM (ScSPM) to convolutional neural networks (CNN)
image_to_klg
this is the code for co-fusion and elastic-fusion, which can convert images to klg file. enjoy it!
kitti_to_rosbag
Dataset tools for working with the KITTI dataset raw data ( http://www.cvlibs.net/datasets/kitti/raw_data.php ) and converting it to a ROS bag. Also allows a library for direct access to poses, velodyne scans, and images.
Make_a_neural_network
This is the code for the "Make a Neural Network" - Intro to Deep Learning #2 by Siraj Raval on Youtube
mini-image-rotation
Super Tiny jQuery 360 Degrees Product Image Viewer
Neural-Network-with-Financial-Time-Series-Data
This solution presents an accessible, non-trivial example of machine learning (Deep learning) with financial time series using TensorFlow
neural-networks-and-deep-learning
Code samples for my book "Neural Networks and Deep Learning"
PREDICTION-OF-CREDIT-RISK-EVALUATION-USING-NAIVE-BAYES-ARTIFICIAL-NEURAL-NETWORK-AND-SUPPORT-VECTOR
An accurate prediction of credit risk evaluation is very useful for the banking and financial industry in minimizing the risk in lending credit to the customer and decreasing the chances of making wrong decision. As the increase in customers and emergence of different trade, it is difficult for bank management to analyze individual physically hence data mining algorithms are implemented in order to reduce the work effort by the bank management. This study attempted to implement three data mining model and compared their performances in predicting the risk in giving credit to the customer. In this study neural network based on back propagation, naive Bayes algorithm and support vector machine were implemented. Eight technical indicators were used as input for the above models. Data preprocessing were done to increase the performance of their prediction. A comparative analysis of the models was carried out and experimental results showed that the performance of Support Vector Machine (92%) was higher than the other two. Naïve Bayes (87%) performance was found little better than that of Artificial Neural Network (85%). Findings from this study can help in improvement of the existing system.
RNN-stocks-prediction
Another attempt to use Deep-Learning in the financial markets
sql-server-samples
Official Microsoft GitHub Repository containing code samples for SQL Server
stockPredictionUsingLSTM
This project is to practice applying Long Short-Term Memory network in deep learning to predict time series financial data. I selected Amazon's stock prices in the past five years and achieved a satisfying prediction result.
TensorFlowSharp
TensorFlow API for .NET languages
TravelPortUniversalAPI
AirTicketing in C#.net MVC 5 api for Ticket Reservation. Travelport Galileo GDS. ... A standardized environment to create an interface to the Travelport Apollo or Travelport Galileo GDS via dedicated line or VPN connection.